• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Future generation computer systems >A new chain coding mechanism for compression stimulated by a virtual environment of a predator-prey ecosystem
【24h】

A new chain coding mechanism for compression stimulated by a virtual environment of a predator-prey ecosystem

机译：捕食者—猎物生态系统虚拟环境刺激的新型压缩链编码机制

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, the researcher introduces a new chain coding mechanism that employs a predator-prey agent-based modeling simulation with some modifications and simplifications and uses it in compression. In the proposed method, an image is ultimately represented by a virtual world consisting of three agent types: wolves, sheep, and paths. While sheep and paths do not change their locations during the program execution, wolves search for sheep to prey on. With each step, a wolf can determine its path by choosing between seven pertinent moves depending on the encountered information. The algorithm keeps track of the wolves' initial locations and their movements and uses this as a new image representation. Additionally, the researcher introduces the 'Lengthy Advance Move,' the purpose of which is to group particular consecutive codes and further reduce the chain. This, in turn, allows the researcher to experiment with different variations of the algorithm. Finally, the researcher applies arithmetic coding on the series of movements for extra compression. The experimental results reveal that the current algorithm generates higher compression ratios than many standardized algorithms, including JBIG family algorithms. Most importantly, paired-sample t-tests reveal significant differences between the findings of the wolf-sheep predation algorithm and the other algorithms used as benchmarks for comparisons. (C) 2019 Elsevier B.V. All rights reserved.
机译：在本文中，研究人员介绍了一种新的链编码机制，该机制采用了基于捕食者-猎物代理的建模仿真，并做了一些修改和简化，并将其用于压缩。在提出的方法中，图像最终由虚拟世界表示，该虚拟世界由三种媒介类型组成：狼，绵羊和路径。尽管在程序执行期间绵羊和路径不会改变其位置，但狼仍在寻找绵羊作为猎物。在每一步中，狼都可以通过根据所遇到的信息在七个相关动作之间进行选择来确定其路径。该算法跟踪狼的初始位置及其运动，并将其用作新的图像表示。此外，研究人员介绍了“长度提前移动”，其目的是将特定的连续代码分组并进一步减少链条。反过来，这使研究人员可以尝试使用该算法的不同变体。最后，研究人员对一系列运动应用算术编码，以进行额外压缩。实验结果表明，与包括JBIG系列算法在内的许多标准算法相比，当前算法产生的压缩率更高。最重要的是，成对样本t检验揭示了狼羊掠食算法与其他用作比较基准的算法之间的显着差异。 （C）2019 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号